Abstract
Future embedded imaging applications will be more demanding processing performance while requiring the same low cost and low energy consumption. This paper presents and evaluates a color-aware instruction set extension (CAX) for single instruction, multiple data (SIMD) processor arrays to meet the computational requirements and cost goals. CAX supports parallel operations on two-packed 16-bit (6:5:5) YCbCr data in a 32-bit datapath processor, providing greater concurrency and efficiency for color image and video processing. Unlike typical multimedia extensions (e.g., MMX, VIS, and MDMX), CAX harnesses parallelism within the human perceptual color space rather than depending solely on generic subword parallelism. Moreover, the ability to reduce data format size reduces system cost. The reduction in data bandwidth also simplifies system design. Experimental results on a representative SIMD array architecture show that CAX achieves a speedup ranging from 5.2× to 8.8× (an average of 6.3×) over the baseline SIMD array performance. This is in contrast to MDMX (a representative MIPS multimedia extension), which achieves a speedup ranging from 3× to 5× (an average of 3.7×) over the same baseline SIMD array. CAX also outperforms MDMX in both area efficiency (a 52% increase versus a 13% increase) and energy efficiency (a 50% increase versus an 11% increase), resulting in better component utilization and sustainable battery life. Furthermore, CAX improves the performance and efficiency with a mere 3% increase in the system area and a 5% increase in the system power, while MDMX requires a 14% increase in the system area and a 16% increase in the system power. These results demonstrate that CAX is a suitable candidate for application-specific embedded multimedia systems.
This work was performed by authors at the Georgia Institute of Technology (Atlanta, GA).
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Kim, J., Wills, D.S., Wills, L.M. (2005). Implementing and Evaluating Color-Aware Instruction Set for Low-Memory, Embedded Video Processing in Data Parallel Architectures. In: Yang, L.T., Amamiya, M., Liu, Z., Guo, M., Rammig, F.J. (eds) Embedded and Ubiquitous Computing – EUC 2005. EUC 2005. Lecture Notes in Computer Science, vol 3824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596356_4
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DOI: https://doi.org/10.1007/11596356_4
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